A Predictive Analysis of Non-Performing Assets Using ARIMA Method- A Case of Government-owned Indian Bank

Abstract

Non-performing assets are a constant economic issue affecting its integrity and stability. In this paper, the researcher aims to analyze the trends and the factors influencing the NPAs in banking sector by using the ARIMA method. By doing an extensive and empirical review of the literature, the study identifies the key factors promoting the rise or increase of NPAs and provides a prediction for better risk management. In this paper, we have used time series data of NPAs in Indian banks. We used publicly available data from RBI from the year 2000 to 2023 from its annual reports. The researcher estimated a time series model like ARIMA on it. In this research study, the findings of the paper are expected to aid policymakers and bankers in reducing and mitigating the risk associated with the impact of NPAs.